Design, implementation and evaluation of clinical studies are complex ventures in which a large number of people and/or institutions are involved. A large volume of data is also produced. The administration complexity for this is immense. Conventionally, automatic study and data management systems are used as central support systems for designing, implementing and evaluating clinical studies.
In one example, all systems supplying data (e.g., imaging systems, electronic patient records, etc.) are integrated into a single study and data management system. The systems supplying data may be spread out over various sites and/or facilities, such as hospitals, doctors'practices, etc.
A conventional study and data management system is configured for each individual study in what is referred to as a setup process. This study-specific configuration is necessary to match relevant data flows from data sources and operating sequences to the requirements of a particular study. Data sources may be associated with the actual principal system (e.g., the study and data management system), and may include, for example, equipment at the clinics.
Results of the configuration performed during a setup process and/or the procedure of the setup process itself may be stored in a study protocol, referred to as Standard Operating Procedures (SOPs), and other documentation.
In adaptive clinical studies having modifiable procedures or courses, relevant configuration of the conventional study and data management system must (at least in part) have a variable system configuration, which is changeable during the course of the study.
Conventionally, the design of a clinical study (e.g., one which is to be implemented in the future) and the parameterization of a corresponding study and data management system are the task of a “principle investigator” or sponsor. The sponsor has access to its own experience with preceding clinical studies (e.g., already concluded or currently running clinical studies), and searches for additional required information for implementing the future study. Future studies, however, may be associated with considerable complexity.